Qwen: Qwen2.5 Coder 7B Instruct
Qwen2.5-Coder-7B-Instruct is a 7B parameter instruction-tuned language model optimized for code-related tasks such as code generation, reasoning, and bug fixing. Based on the Qwen2.5 architecture, it incorporates enhancements like RoPE, SwiGLU, RMSNorm, and GQA attention with support for up to 128K tokens using YaRN-based extrapolation. It is trained on a large corpus of source code, synthetic data, and text-code grounding, providing robust performance across programming languages and agentic coding workflows. This model is part of the Qwen2.5-Coder family and offers strong compatibility with tools like vLLM for efficient deployment. Released under the Apache 2.0 license.
Context Window
33K
Input Price
$0.0300/M tokens
Output Price
$0.0900/M tokens
Modality
text->text
Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.000390
~25K
Words Equivalent
~16
Pages of Text
~328
Code Functions
Related Categories:
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